The candidate has a primary interest in investigating the associations between neighborhood socioeconomic (SES) environments, behavioral and psychosocial risk factors, and cardiovascular disease (CVD). The mentored phase will include coursework in Geographic Information Systems (GIS) and complex multilevel modeling, as well as data linkages prior to the independent phase project. The independent phase will establish the candidate's independence while enabling skill development in GIS and multilevel modeling. Data on nearly 90,000 women from the Harvard-based Nurses' Health Study, a well-established cohort, and nationally-representative data on approximately 262,000 men and 314,000 women from the National Health Interview Survey, will be analyzed using multilevel discrete-time survival analysis models to estimate the relations between neighborhood SES and risks of non-fatal and fatal coronary heart disease (CHD), and to test for the presence of behavioral and psychosocial mediators. Furthermore, GIS methods will be used to assess whether some of these mediators may be determined by particular neighborhood services and amenities. By contributing to the knowledge base on the neighborhood determinants of and pathways to CHD, the project's efforts may ultimately translate through interventions into more effective reductions in CVD burden among Americans. This award should enable the candidate to pursue a successful career in the study of the neighborhood determinants of CVD.